叶面积指数(leaf area index,LAI)在山地森林具有高度的空间异质性.基于大样地尺度的山地森林叶面积空间异质性的研究较少,而且不涉及LAI对地形的响应研究.基于LAI的空间异质性和地形因子的相关性,确定取样尺度,可为提升区域尺度上LAI的空间遥感精度提供依据.本研究依托祁连山大野口流域10.2 ha(340 m×300 m)的青海云杉林动态监测样地,使用CID CI-110植物冠层数字图像分析仪对样地内255个20 m×20 m样方进行五点法LAI测定,分析LAI的空间异质性特征和空间分布格局及其与地形因子的相关性.研究结果表明:(1)LAI具有中等变异性,指数模型是变异函数的最佳理论模型,具有强烈的空间自相关,变程为16 m,南—北方向上是LAI分布的优势格局.(2)LAI的空间分布格局相对简单,具有一定的斑块性,LAI为0.56～1.43的斑块所占面积最大.(3)LAI与海拔和坡度均呈极显著负相关(P＜0.01),与坡度和曲率的相关性均不显著(P＞0.05).(4)青海云杉林的LAI空间异质性与尺度和方向有关,部分地形因子对LAI存在着显著影响.研究结果可为青海云杉林生态过程分析以及遥感技术反演LAI参数提供依据.
Spatial Heterogeneity of Leaf Area Index of Picea Crassifolia Forest in the Qilian Mountains,China
The leaf area index(LAI)serves as a primary parameter characterizing forest ecological processes and structural features.LAI has high spatial heterogeneity in mountain forests.Studies of spatial heterogeneity of leaf area in montane forests based on sample plot of a large scale were scarce and did not investigate the dependency of LAI on topography.Determining the sampling scale based on spatial heterogeneity of LAI and its correlation with topographic factors can provide an accuracy calibration of spatial remote sensing of LAI on a regional scale.This study was exemplified by dynamic monitoring plots of Picea crassifolia forest built in the Dayekou watershed of the Qilian Mountains,northwestern China,covering an area of 10.2 hectares(340 m×300 m).LAI at 255 plots of 20 m×20 m in size was determined by five-point method using CID CI-110 plant canopy digital imaging analyzer.Then the spatial heterogeneity and spatial distribution pattern of LAI and its correlation with terrain factors were analyzed.(1)LAI exhibited moderate variability,whose variogram function could be interpreted by an exponential model as the optimal theoretical model,which had strong spatial autocorrelation with a variable range of 16 meters,and the dominant pattern of LAI distribution was in the south-north direction.(2)The spatial distribution pattern of LAI is relatively simple,exhibiting certain patchiness,with the largest area occupied by patches of LAI ranging from 0.56 to 1.43.(3)LAI is significantly negatively correlated with altitude and slope(P＜0.01),while its correlation with slope and curvature is not significant(P＞0.05).(4)The spatial heterogeneity of LAI in Picea crassifolia forests is related to scale and direction,with certain topographic factors exerting significant influence on LAI.The study provides a basis for the analysis of ecological processes of Picea crassifolia forest in the Qilian Mountains and the determination of LAI parameters in remote sensing techniques.
Picea crassifolia forestdynamics monitoring plotleaf area indexspatial heterogeneity
万方数据
维普
